Question

我正在尝试使用Tensor Flow构建一个简单的逻辑回归，但是我收到了这个错误：

TypeError: 'Series' objects are mutable, thus they cannot be hashed

这是我的代码：

data = pd.read_csv(data_file,sep=";",names=header)
...
n = data.shape[0]
n_training_set = int(.7*n)
df_train = data[30:n_training_set]
df_test = data[n_training_set:]

LABEL_COLUMN = 'action'


CONTINUOUS_COLUMNS = ['rsi','stochk','stochd']
CATEGORICAL_COLUMNS = []

def input_fn(df):
  # Creates a dictionary mapping from each continuous feature column name (k) to
  # the values of that column stored in a constant Tensor.
  continuous_cols = {k: tf.constant(df[k].values)
                     for k in CONTINUOUS_COLUMNS}
  # Creates a dictionary mapping from each categorical feature column name (k)
  # to the values of that column stored in a tf.SparseTensor.
  categorical_cols = {k: tf.SparseTensor(
      indices=[[i, 0] for i in range(df[k].size)],
      values=df[k].values,
      dense_shape=[df[k].size, 1])
                      for k in CATEGORICAL_COLUMNS}
  # Merges the two dictionaries into one.
  feature_cols = dict(continuous_cols.items() + categorical_cols.items())
  # Converts the label column into a constant Tensor.
  label = tf.constant(df[LABEL_COLUMN].values)
  # Returns the feature columns and the label.
  return feature_cols, label


def train_input_fn():
  return input_fn(df_train)

def eval_input_fn():
  return input_fn(df_test)

model_dir = tempfile.mkdtemp()

CONTINUOUS_COLUMNS = ['rsi','stochk','stochd']

rsi = tf.contrib.layers.real_valued_column(df_train["rsi"])
stochk = tf.contrib.layers.real_valued_column(df_train["stochk"])
stochd = tf.contrib.layers.real_valued_column(df_train["stochd"])

### defining the model
m = tf.contrib.learn.LinearClassifier(feature_columns=[
        rsi,
        stochk,
        stochd

    ],
  model_dir=model_dir)


m.fit(input_fn=train_input_fn, steps=200)

我该如何解决这个问题？

Answer 1

你的错误就在附近：

rsi = tf.contrib.layers.real_valued_column(df_train["rsi"])
stochk = tf.contrib.layers.real_valued_column(df_train["stochk"])
stochd = tf.contrib.layers.real_valued_column(df_train["stochd"])

这里您从pandas数据框中作为第一个参数传递一个列，但第一个参数tot real_valued_column应该是该列的名称。因此将上面的行替换为：

rsi = tf.contrib.layers.real_valued_column("rsi")
stochk = tf.contrib.layers.real_valued_column("stochk")
stochd = tf.contrib.layers.real_valued_column("stochd")

应该诀窍。

另请参阅本教程的section。

Tensorflow TypeError：'Series'对象是可变的，因此它们不能被散列

1 个答案: